• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1345-1362
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• 2019

Most active queue management algorithms manage network congestion based on the size of the queue but ignore the network environment which makes queue size change. It seriously affects the response speed of the algorithm. In this paper, a new AQM algorithm named CT-AQM (Change Trend-Adaptive Queue Management) is proposed. CT-AQM predicts the change trend of queue size in the soon future based on the change rate of queue size and the network environment, and optimizes its dropping function. Simulation results indicate that CT-AQM scheme has a significant improvement in loss-rate and throughput.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.93-105
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• 2006

The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of nonintuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.133-146
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• 2004

Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.177-183
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• 2007

Active queue management (AQM) refers to a family of packet dropping mechanisms for router queues that has been proposed to support end-to-end congestion control mechanisms in the Internet. The proposed AQM algorithm by the IETF is Random Early Detection (RED). The RED algorithm allows network operators simultaneously to achieve high throughput and low average delay. However. the resulting average queue length is quite sensitive to the level of congestion. In this paper, we propose the Refined Adaptive RED(RARED), as a solution for reducing the sensitivity to parameters that affect RED performance. Based on simulations, we observe that the RARED scheme improves overall performance of the network. In particular, the RARED scheme reduces packet drop rate and improves goodput.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.123-133
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• 2023

Active queue management (AQM) is a leading congestion control system, which can keep smaller queuing delay, less packet loss with better network utilization and throughput by intentionally dropping the packets at the intermediate hubs in TCP/IP (transmission control protocol/Internet protocol) networks. To accelerate the responsiveness of AQM framework, proportional-integral-differential (PID) controllers are utilized. In spite of its simplicity, it can effectively take care of a range of complex problems; however it is a lot complicated to track down optimal PID parameters with conventional procedures. A few new strategies have been grown as of late to adjust the PID controller parameters. Therefore, in this paper, we have developed a Squirrel search based PID controller to dynamically find its controller gain parameters for AQM. The controller gain parameters are decided based on minimizing the integrated-absolute error (IAE) in order to ensure less packet loss, high link utilization and a stable queue length in favor of TCP networks.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.417-424
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• 2003

In this paper, we introduce and analyze a feedback control model of TCP/AQM dynamics. Then, we propose the Pro-active Queue Management (PAQM) mechanism, which can provide proactive congestion avoidance and control using an adaptive congestion indicator and a control function for wide range of traffic environments. The PAQM stabilizes the queue length around a desired level while giving smooth and low packet loss rates independent of the traffic load level under a wide range of traffic environment. The PAQM outperforms other AQM algorithms such as Random Early Detection (RED) [1] and PI-controller [2]

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.19-23
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• 2008

The AQM (Active Queue Management) starts dropping packets earlier to notify traffic sources about the incipient stage of congestion. The AQM improves fairness between response flow (like TCP) and non-response flow (like UDP), and it can provide high throughput and link efficiency. In this paper, we suggest the QVARED (Queue Variation Adaptive RED) algorithm to respond to bursty traffic more actively. It is possible to provide more smoothness of average queue length and the maximum packet drop probability compared to RED and ARED (Adaptive RED). Therefore, it is highly adaptable to new congestion condition. Our simulation results show that the drop rate of QVARED is decreased by 80% and 40% compare to those of RED and ARED, respectively. This results in shorter end-to-end delay by decreasing the number of retransmitted packets. Also, the QVARED reduces a bias effect over 18% than that of drop-tail method; therefore packets are transmitted stably in the bursty traffic condition.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.1-77
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• 2001

In this paper, we propose a control scheme for improving the performance of a conventional Proportional-Integral (PI) controller for Active Queue Management (AQM) supporting TCP flows. When the PI controller is used for AQM, the windup phenomenon of the integral action causes the performance degradation. Therefore we model AQM as a system with a saturator and apply anti-windup methods to the PI controller for AQM. We compare the performances of anti-windup algorithm with the conventional PI controller through ns simulations. The simulation results show that the PI controller with anti-windup method performs better than the conventional PI controller.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.80-91
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• 2010

Due to the convergence of broadcasting and communications, IPTV services are spotlighted as the that next-generation multimedia services. IPTV services should have functionality such as unlimited channel capacity, extension of media, QoS awareness and are required increasing traffic and quality control technology to adapt the attributes of IPTV service. Consequently, flow based quality control techniques are needed. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED(Random Early Detection) and modified RED algorithms have proposed. However, these algorithms have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the Flow based AQM(Active Queue Management) algorithm for the multimedia services that request various QoS requirements. The proposed algorithm can converge the packet loss ratio to the target packet loss ratio of required QoS requirements. And we present a performance evaluation by the simulations using the ns-2.